I've joined folding@home few weeks ago and it's run just fine. Yesterday I've decided to compare my system with other gentlemen's hardware to ensure I've made proper setup and my hardware runs at optimal level. I've discovered that most commonly used metric (and the only metric I've found database for) is Parrots Per Day. The itself database is published here:

But the results I've got was quite discouraging. According the database my average performance should be 146,814 PPD (Radeon HD 7970) per unit. I have two 7970 watercooled to 60°C, running 24x7 at stock frequencies and monitoring tool indicates constant 97-99% load. My results is about 23-24k PPD per unint (about 49k in total). This is more than 6 times slower than average performance reported by other users with same hardware. How could such thing be? Is PPD reliable enough to compare computing performance in F@H, or some other metrics should be used?

I'm not looking towards Parrots them self, but 6-times difference make me think that I've did something extremely wrong.

Usually such a large discrepancy in expected points versus what is received is due to not using a passkey. A passkey is required to get the Quick Return Bonus, for faster GPU's these bonus points are a significant part of the PPD being reported. Please see the Passkey FAQ. With a passkey it takes the successful return of 10 WU's before the QRB is awarded for future WU's as long as at least an 80% return rate is maintained.

I agree with the passkey assessments; however, as a side note:That "database" is only meant to compare 1 specific PRGC on 1 specific card at a time.i.e.:Project10494, Run5, Clone36, Generation303 performed on CardX compared to Project10494, Run5, Clone36, Generation303 performed on CardX

maybe you took fairly large WU: most of the point you will make with a GPU is based on how fast you complete the WU compared to the time it's expected to finish.if a WU timeout in 10 days but you finish it in an hour, you will likely get 10 times the base credit, if your WU takes more time, you get a lot less bonus and thus a lot less PPD.

HagegeR wrote:maybe you took fairly large WU: most of the point you will make with a GPU is based on how fast you complete the WU compared to the time it's expected to finish.if a WU timeout in 10 days but you finish it in an hour, you will likely get 10 times the base credit, if your WU takes more time, you get a lot less bonus and thus a lot less PPD.

That could be too. So much is wrong with most conversations that revolve around that damn sheet (especially since it rarely gets updated and all of the updates come from posts in a single forum); I want to scream every time someone mentions it.

Thank your for reply, gentelmen. I've added my passkey and my PPD jumped close to the database values almost instantly.

Now, knowing that Parrots Per Day not just raw folding performance metric but fancy combination of different factors such as "Quick Return Bonus", second question comes into play. How good is it for comparing performance and how does it scaled? For example, if my graphic card runs at 146K PPD at average and GTX Titan X Pascal runs at 1442K PPD does than mean that GTX Titan X Pascal will complete same folding workunit 10 times faster?

If I understood correctly, PPD is not even linear. Practically this could mean that dual GTX 1070 could do more job, than one GTX Titan X Pascal, despite the GTX Titan X Pascal will produce more PPD.

On the other hand, PPD formula was picked by project authors to reflect project's actual needs. They should be aware of impact of the PPD formula when new user deciedes which hardware to use. Current formula stimulates to use fewer but faster GPU than more but less fast, despite the fact that raw throughout could be lower. Probably, project authors have good reason to do it in this way, which I not aware though.

schernichkin wrote:If I understood correctly, PPD is not even linear. Practically this could mean that dual GTX 1070 could do more job, than one GTX Titan X Pascal, despite the GTX Titan X Pascal will produce more PPD.

That's true. It's easiest to explain if I talk about WUs for the CPU, but the same answer applies to GPUs.

Suppose your system has multiple CPUs and you complete two similar WUs. You have a choice between allocating all of your CPUs to one project at a time or splitting the resources so that both WUs are being processed concurrently. Using all of your CPUs, let's say the WU is completed in a day but using half of your resources, each WU will take two days. Completing a WU in one day and a different WU on the next day moves science along faster than delaying each of them by an extra day -- and the Quick Return Bonus (QRB) reflects that fact.